This disclosure relates generally to the field of image processing. More particularly, this disclosure relates to a technique for enhancing images using a novel type of histogram referred to herein as a Structure Histogram.
Image enhancement may be thought of the process of altering an image to make it more aesthetically pleasing. Illustrative image enhancement operations include those that correct color hue and brightness imbalances as well as other image editing features, such as red eye removal, sharpness adjustments, zoom features and automatic cropping. Common to many of these operations is the use of histograms. Conventional image histograms provide a graphical representation of the distribution of pixel values in an image. Referring to FIG. 1, normalized conventional histogram 100 for an 8-level gray scale image having pixel values between 0 and 7 is shown. (As used here, the term “normalized” refers to the case where histogram entries, or bin values, have been adjusted so that the area under the histogram is equal 1.0.) Histogram 100 shows that 50% of the pixels have a gray scale value of 2, 20% of the pixels have gray scale values of 3 another 20% have a gray scale value of 4, and 10% of the pixels have a gray scale value of 7.
Conventional histograms such as histogram 100 are, by definition, completely insensitive to the ordering of pixels in an image. (See discussion below with regards to Table 1.) For example, FIG. 2A shows gray scale image 200 of a baby, FIG. 2B shows the corresponding conventional histogram 205, and FIG. 2C shows image 210 that results from ordering/sorting the pixels that make up image 200 (e.g., from smallest/darkest to largest/brightest). Because images 200 and 210 are composed of the same pixels, their histograms are identical (see conventional histogram 205). The images are, however, clearly different and the person capturing the images would presumably want to enhance the images differently. While conventional histograms may be well-suited to aid in some enhancement operations, FIG. 2 illustrates the difficulty of relying on them to perform all image enhancement operations.